Energy-Efficient Precoding Design for Downlink IRS-Assisted URLLC System

Abstract

Ultra-reliable and low-latency communication (URLLC) has emerged as a crucial usage scenario for fifth-generation (5G)-and-beyond networks and has become an important enabler of Internet of Things (IoT). Because most devices in URLLC have limited energy resources, energy-efficient design is also a significant topic in URLLC systems. On the other hand, Intelligent reflecting surface (IRS) is a promising alternative to improve system performance due to its well energy-efficiency (EE). It is expected that the IRS can play a key role in URLLC systems. This paper studies a downlink IRS-assisted URLLC system with single user, in which the problem is formulated as an energy-efficiency maximization problem. The optimization problem is non-convex and we propose an algorithm based on successive convex approximation (SCA) and semi-definite relaxation (SDR) techniques to obtain a suboptimal solution of the proposed problem. Finally, the simulation results are shown to verify the effectiveness of the proposed algorithm and the positive impact of IRS on the URLLC system.